AWS Machine Learning Blog

Category: Advanced (300)

Generate unique images by fine-tuning Stable Diffusion XL with HAQM SageMaker

Stable Diffusion XL by Stability AI is a high-quality text-to-image deep learning model that allows you to generate professional-looking images in various styles. Managed versions of Stable Diffusion XL are already available to you on HAQM SageMaker JumpStart (see Use Stable Diffusion XL with HAQM SageMaker JumpStart in HAQM SageMaker Studio) and HAQM Bedrock (see […]

Build a self-service digital assistant using HAQM Lex and HAQM Bedrock Knowledge Bases

Organizations strive to implement efficient, scalable, cost-effective, and automated customer support solutions without compromising the customer experience. Generative artificial intelligence (AI)-powered chatbots play a crucial role in delivering human-like interactions by providing responses from a knowledge base without the involvement of live agents. These chatbots can be efficiently utilized for handling generic inquiries, freeing up […]

Build a conversational chatbot using different LLMs within single interface – Part 1

With the advent of generative artificial intelligence (AI), foundation models (FMs) can generate content such as answering questions, summarizing text, and providing highlights from the sourced document. However, for model selection, there is a wide choice from model providers, like HAQM, Anthropic, AI21 Labs, Cohere, and Meta, coupled with discrete real-world data formats in PDF, […]

AI-powered assistants for investment research with multi-modal data: An application of HAQM Bedrock Agents

This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Financial analysts and research analysts in capital markets distill business insights from financial and non-financial data, […]

Improve visibility into HAQM Bedrock usage and performance with HAQM CloudWatch

In this blog post, we will share some of capabilities to help you get quick and easy visibility into HAQM Bedrock workloads in context of your broader application. We will use the contextual conversational assistant example in the HAQM Bedrock GitHub repository to provide examples of how you can customize these views to further enhance visibility, tailored to your use case. Specifically, we will describe how you can use the new automatic dashboard in HAQM CloudWatch to get a single pane of glass visibility into the usage and performance of HAQM Bedrock models and gain end-to-end visibility by customizing dashboards with widgets that provide visibility and insights into components and operations such as Retrieval Augmented Generation in your application.

Evaluate the reliability of Retrieval Augmented Generation applications using HAQM Bedrock

In this post, we show you how to evaluate the performance, trustworthiness, and potential biases of your RAG pipelines and applications on HAQM Bedrock. HAQM Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and HAQM through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Maximize your HAQM Translate architecture using strategic caching layers

In this post, we explain how setting up a cache for frequently accessed translations can benefit organizations that need scalable, multi-language translation across large volumes of content. You’ll learn how to build a simple caching mechanism for HAQM Translate to accelerate turnaround times.

Boost productivity with video conferencing transcripts and summaries with the HAQM Chime SDK Meeting Summarizer solution

Businesses today heavily rely on video conferencing platforms for effective communication, collaboration, and decision-making. However, despite the convenience these platforms offer, there are persistent challenges in seamlessly integrating them into existing workflows. One of the major pain points is the lack of comprehensive tools to automate the process of joining meetings, recording discussions, and extracting […]